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  • 1
    Online Resource
    Online Resource
    Ubiquity Press, Ltd. ; 2021
    In:  Journal of Open Research Software Vol. 9, No. 1 ( 2021-10-19), p. 29-
    In: Journal of Open Research Software, Ubiquity Press, Ltd., Vol. 9, No. 1 ( 2021-10-19), p. 29-
    Type of Medium: Online Resource
    ISSN: 2049-9647
    Language: Unknown
    Publisher: Ubiquity Press, Ltd.
    Publication Date: 2021
    detail.hit.zdb_id: 2740435-3
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  • 2
    Online Resource
    Online Resource
    Cambridge University Press (CUP) ; 2021
    In:  Journal of Glaciology Vol. 67, No. 262 ( 2021-04), p. 313-330
    In: Journal of Glaciology, Cambridge University Press (CUP), Vol. 67, No. 262 ( 2021-04), p. 313-330
    Abstract: The Kaskawulsh Glacier is an iconic outlet draining the icefields of the St. Elias Mountains in Yukon, Canada. We determine and attempt to interpret its catchment-wide mass budget since 2007. Using SPOT5/6/7 data we estimate a 2007–18 geodetic balance of −0.46 ± 0.17 m w.e. a −1 . We then compute balance fluxes and observed ice fluxes at nine flux gates to examine the discrepancy between the climatic mass balance and internal mass redistribution by glacier flow. Balance fluxes are computed using a fully distributed mass-balance model driven by downscaled and bias-corrected climate-reanalysis data. Observed fluxes are calculated using NASA ITS_LIVE surface velocities and glacier cross-sectional areas derived from ice-penetrating radar data. We find the glacier is still in the early stages of dynamic adjustment to its mass imbalance. We estimate a committed terminus retreat of ~23 km under the 2007–18 climate and a lower bound of 46 km 3 of committed ice loss, equivalent to ~15% of the total glacier volume.
    Type of Medium: Online Resource
    ISSN: 0022-1430 , 1727-5652
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2140541-4
    SSG: 14
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  • 3
    In: Journal of Climate, American Meteorological Society, Vol. 36, No. 18 ( 2023-09-15), p. 6141-6161
    Abstract: A 10-member ensemble simulation with the NASA GISS-E2-1-G climate model shows a clear bifurcation in the Atlantic meridional overturning circulation (AMOC) strength under the SSP2–4.5 extended scenario. At 26°N, the bifurcation leads to 8 strong AMOC and 2 much weaker AMOC states, while at 48°N, it leads to 8 stable AMOC-on and 2 nearly AMOC-off states, the latter lasting approximately 800 years. A variety of fully coupled models have demonstrated tipping points in AMOC through hosing experiments, i.e., prescribing sufficient freshwater inputs in the subpolar North Atlantic. In the GISS simulations, there are no external freshwater perturbations. The bifurcation arises freely in the coupled system and is the result of stochastic variability (noise-induced bifurcation) associated with sea ice transport and melting in the Irminger Sea after a slowing of the greenhouse gas forcing. While the AMOC strength follows the near shutdown of the Labrador Sea deep convection initially, the Irminger Sea salinity and deep mixing determine the timing of the AMOC recovery or near collapse at 48°N, which varies widely across the ensemble members. Other feedbacks such as ice-albedo, ice-evaporation, E − P , and the overturning salt-advection feedback play a secondary role that may enhance or reduce the primary mechanism which is ice melt. We believe this is the first time that a coupled climate model has shown such a bifurcation across an initial condition ensemble and might imply that there is a chance for significant and prolonged AMOC slow down due to internal variability of the system. Significance Statement We believe this is the first time that divergent AMOC behavior has been reported for an ensemble of Earth system model simulations using identical climate forcing and no prescribed freshwater perturbations. This response is a manifestation of noise-induced bifurcation, enhanced by feedbacks, revealing the role stochastic (or intrinsic) variability may play in AMOC stability.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2023
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 4
    Online Resource
    Online Resource
    Copernicus GmbH ; 2018
    In:  Earth System Science Data Vol. 10, No. 1 ( 2018-03-27), p. 609-626
    In: Earth System Science Data, Copernicus GmbH, Vol. 10, No. 1 ( 2018-03-27), p. 609-626
    Abstract: Abstract. In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the “ocean carbon states”, as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical–subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air–sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias. All data and analysis scripts are available at https://data.giss.nasa.gov/oceans/carbonstates/ (DOI: https://doi.org/10.5281/zenodo.996891).
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2475469-9
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